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Debugging in R

Target Audience
Expected Duration
Lesson Objectives
Course Number

One of the most important tasks in any programming language or development environment is debugging. In this course, you'll discover ways you can debug R code and improve the resilience of your R programs through defensive programming.

Target Audience
Individuals with some R and data science experience working toward a wider degree of knowledge in using R for data science


Expected Duration (hours)

Lesson Objectives

Debugging in R

  • start the course
  • debug R code with RStudio
  • use the traceback function to examine the call stack
  • use browser to step through R code
  • use R warning and message functions
  • implement handlers for debugging
  • use the microbenchmark library to benchmark R performance
  • identify methods of defensive programming in R
  • set your R program to report warnings as errors for debugging
  • implement asserts in R
  • use the pryr library to examine memory use in R
  • trace address and reference information in R using pryr
  • add the browser function to some R code to debug it
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